Interesting case of regional left ventricular hypertrophy.

This is an account of an interesting case with an unusual cardiac presentation. He is a man in his 60s who presented with chest tightness to the accident and emergency unit. The initial thoughts were of acute coronary syndrome or acute aortic syndrome. The initial set of investigations was non-conclusive. His echocardiogram which was done during hospital admission showed asymmetric hypertrophy of the heart muscle. It was prudent to assess that new finding with an MRI scan. The patient presented to the hospital twice during the investigation and was treated for a lower respiratory tract infection. The MRI report showed an interventricular mass lesion extending to the right ventricular free wall with angiosarcoma being high up in the differential diagnosis. Going through the heart team discussion, the decision was to go for a transcatheter biopsy. The biopsy showed B-cell lymphoma. The treatment started and interestingly with satisfactory results.

Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers.

Left ventricular hypertrophy (LVH) is a hypertensive heart disease that significantly escalates the risk of clinical cardiovascular events. Its etiology potentially incorporates various clinical attributes such as gender, age, and renal function. From mechanistic perspective, the remodeling process of LVH can trigger increment in certain biomarkers, notably sST2 and NT-proBNP. This multicenter, retrospective study aimed to construct an LVH risk assessment model and identify the risk factors. A total of 417 patients with essential hypertension (EH), including 214 males and 203 females aged 31-80 years, were enrolled in this study; of these, 161 (38.6%) were diagnosed with LVH. Based on variables demonstrating significant disparities between the LVH and Non-LVH groups, three multivariate stepwise logistic regression models were constructed for risk assessment: the "Clinical characteristics" model, the "Biomarkers" model (each based on their respective variables), and the "Clinical characteristics + Biomarkers" model, which amalgamated both sets of variables. The results revealed that the "Clinical characteristics + Biomarkers" model surpassed the baseline models in performance (AUC values of the "Clinical characteristics + Biomarkers" model, the "Biomarkers" model, and the "Clinical characteristics" model were .83, .75, and .74, respectively; P < .0001 for both comparisons). The optimized model suggested that being female (OR: 4.26, P <.001), being overweight (OR: 1.88, p = .02) or obese (OR: 2.36, p = .02), duration of hypertension (OR: 1.04, P = .04), grade III hypertension (OR: 2.12, P < .001), and sST2 (log-transformed, OR: 1.14, P < .001) were risk factors, while eGFR acted as a protective factor (OR: .98, P = .01). These findings suggest that the integration of clinical characteristics and biomarkers can enhance the performance of LVH risk assessment.

Cardio-Ankle Vascular Index as a Marker of Left Ventricular Hypertrophy in Treated Hypertensives: Findings From the Pamela Study.

BACKGROUND: Findings regarding the association between Cardio-Ankle Vascular Index (CAVI) and cardiac hypertension-mediated organ damage (HMOD), such as left ventricular hypertrophy (LVH) assessed by echocardiography, in elderly hypertensive patients are scanty. We sought to investigate this issue in the hypertensive fraction of the general population treated with anti-hypertensive drugs enrolled in the Pressioni Monitorate E Loro Associazioni (PAMELA) study. METHODS: The study included 239 out of 562 participants who attended the second and third surveys of the PAMELA study performed after 10 and 25 years from the initial evaluation. Data collection included medical history, anthropometric parameters, office, home, ambulatory blood pressure (BP), blood examinations, echocardiography, and CAVI measurements. RESULTS: In the whole study sample (age 69 ±â€…9 years, 54% males), CAVI was positively correlated with age, office, home, ambulatory systolic BP, LV mass (LVM) index, and negatively associated with body mass index (BMI). In multivariate analysis, CAVI was associated with the LVM index (P < 0.05) independently of major confounders. The participants with LVH exhibited significantly higher CAVI (10.6 ±â€…2.8 vs. 9.2 ±â€…1.8 m/s P < 0.001), larger left atrial diameter, and lower LV ejection fraction values than their counterparts without it. The CAVI value of 9.4 m/s was the best cut-off for prediction of LVH in the whole sample. CONCLUSIONS: Our study provides new evidence of an independent association between CAVI and LVH in treated elderly hypertensive patients and suggests that the use of this metric of arterial stiffness could not only be used to evaluate vascular damage but also to stratify the risk of LVH.

Electrophysiological Characterization of Subclinical and Overt Hypertrophic Cardiomyopathy by Magnetic Resonance Imaging-Guided Electrocardiography.

BACKGROUND: Ventricular arrhythmia in hypertrophic cardiomyopathy (HCM) relates to adverse structural change and genetic status. Cardiovascular magnetic resonance (CMR)-guided electrocardiographic imaging (ECGI) noninvasively maps cardiac structural and electrophysiological (EP) properties. OBJECTIVES: The purpose of this study was to establish whether in subclinical HCM (genotype [G]+ left ventricular hypertrophy [LVH]-), ECGI detects early EP abnormality, and in overt HCM, whether the EP substrate relates to genetic status (G+/G-LVH+) and structural phenotype. METHODS: This was a prospective 211-participant CMR-ECGI multicenter study of 70 G+LVH-, 104 LVH+ (51 G+/53 G-), and 37 healthy volunteers (HVs). Local activation time (AT), corrected repolarization time, corrected activation-recovery interval, spatial gradients (GAT/GRTc), and signal fractionation were derived from 1,000 epicardial sites per participant. Maximal wall thickness and scar burden were derived from CMR. A support vector machine was built to discriminate G+LVH- from HV and low-risk HCM from those with intermediate/high-risk score or nonsustained ventricular tachycardia. RESULTS: Compared with HV, subclinical HCM showed mean AT prolongation (P = 0.008) even with normal 12-lead electrocardiograms (ECGs) (P = 0.009), and repolarization was more spatially heterogenous (GRTc: P = 0.005) (23% had normal ECGs). Corrected activation-recovery interval was prolonged in overt vs subclinical HCM (P < 0.001). Mean AT was associated with maximal wall thickness; spatial conduction heterogeneity (GAT) and fractionation were associated with scar (all P < 0.05), and G+LVH+ had more fractionation than G-LVH+ (P = 0.002). The support vector machine discriminated subclinical HCM from HV (10-fold cross-validation accuracy 80% [95% CI: 73%-85%]) and identified patients at higher risk of sudden cardiac death (accuracy 82% [95% CI: 78%-86%]). CONCLUSIONS: In the absence of LVH or 12-lead ECG abnormalities, HCM sarcomere gene mutation carriers express an aberrant EP phenotype detected by ECGI. In overt HCM, abnormalities occur more severely with adverse structural change and positive genetic status.

Prediction of cardiovascular events in older patients with hypertension in primary care: a cohort study.

BACKGROUND: Accurate risk stratification identifying patients with hypertension at risk of future cardiovascular disease in primary care would be desirable. AIM: To investigate the association between elevated brain natriuretic peptide (BNP), left ventricular hypertrophy (LVH) on an electrocardiogram (ECG), and LVH on an echocardiogram and the development of cardiovascular events (CVEs), especially heart failure and all-cause mortality (ACM), in a primary care population with hypertension without symptoms of heart failure. DESIGN AND SETTING: A prospective cohort study in five Dutch general practices between 2010-2012 and 2020. METHOD: In total, 530 patients (aged 60-85 years) underwent laboratory testing, ECGs, and echocardiograms at baseline. The incidence of new CVEs and ACM at up to 9 years' follow-up was recorded by data extraction from the digital information systems. RESULTS: Among the 530 participants, 31 (5.8%) developed a coronary event, 44 (8.3%) a cerebrovascular accident, 53 (10.0%) atrial fibrillation, 23 (4.3%) heart failure, and 66 (12.5%) died. Cox regression analyses, adjusting for relevant Framingham covariates, showed that elevated BNP increased the risk of ACM, CVEs, and specifically heart failure independently by 44% (hazard ratio [HR] 1.44, 95% confidence interval [CI] = 1.07 to 1.94, P = -0.017), 45% (HR 1.45, 95% CI = 1.15 to 1.82, P = 0.002), and 288% (HR 3.88, 95% CI = 2.13 to 7.10, P<0.001), respectively. LVH on ECG increased the risk of ACM independently by 108% (HR 2.08, 95% CI = 1.14 to 3.81, P = 0.017). LVH either on an ECG and/or echocardiogram increased the risk of heart failure independently by 309% (HR 4.09, 95% CI = 1.34 to 12.49, P = 0.014). CONCLUSION: In primary care patients with hypertension, BNP seems to be an important marker predicting future CVEs, especially heart failure, as well as all-cause mortality.

Association of baseline electrocardiographic left ventricular hypertrophy with future renal function decline in the general population.

Electrocardiographic left ventricular hypertrophy (LVH) could predict adverse renal outcomes in patients with hypertension. This study aimed to investigate the association between electrocardiographic LVH and future decline in renal function in the general population using a dataset of population-based health checkups from 2010 to 2019 including 19,825 participants. Electrocardiographic LVH was defined according to the Minnesota code. Renal function decline was defined as a decrease of ≥ 25% in the estimated glomerular filtration rate from baseline to < 60 mL/min/1.73 m2. Electrocardiographic LVH was found in 1263 participants at the baseline visit. The mean follow-up period was 3.4 ± 1.9 years. The incidence rates of renal function decline were 0.30 and 0.78 per 100 person-years in the non-LVH group and LVH groups, respectively. Electrocardiographic LVH was associated with the risk for renal function decline in the adjusted analysis (hazard ratio 1.69, 95% confidence interval 1.14-2.50, P = 0.009). This association was comparable across subgroups stratified by age, sex, body mass index, diagnosed hypertension, systolic blood pressure, hemoglobin A1c, and urinary protein. This study underscores the usefulness of electrocardiographic LVH to detect high-risk individuals for renal function decline in the setting of health checkups in the general population.

ISE/ISHNE expert consensus statement on the ECG diagnosis of left ventricular hypertrophy: The change of the paradigm.

The ECG diagnosis of LVH is predominantly based on the QRS voltage criteria. The classical paradigm postulates that the increased left ventricular mass generates a stronger electrical field, increasing the leftward and posterior QRS forces, reflected in the augmented QRS amplitude. However, the low sensitivity of voltage criteria has been repeatedly documented. We discuss possible reasons for this shortcoming and proposal of a new paradigm. The theoretical background for voltage measured at the body surface is defined by the solid angle theorem, which relates the measured voltage to spatial and non-spatial determinants. The spatial determinants are represented by the extent of the activation front and the distance of the recording electrodes. The non-spatial determinants comprise electrical characteristics of the myocardium, which are comparatively neglected in the interpretation of the QRS patterns. Various clinical conditions are associated with LVH. These conditions produce considerable diversity of electrical properties alterations thereby modifying the resultant QRS patterns. The spectrum of QRS patterns observed in LVH patients is quite broad, including also left axis deviation, left anterior fascicular block, incomplete and complete left bundle branch blocks, Q waves, and fragmented QRS. Importantly, the QRS complex can be within normal limits. The new paradigm stresses the electrophysiological background in interpreting QRS changes, i.e., the effect of the non-spatial determinants. This postulates that the role of ECG is not to estimate LV size in LVH, but to understand and decode the underlying electrical processes, which are crucial in relation to cardiovascular risk assessment.

ECG left ventricular hypertrophy in aortic stenosis: Relationship with cardiac structure, invasive hemodynamics, and long-term mortality.

BACKGROUND: In aortic stenosis (AS), left ventricular hypertrophy (LVH) is the response to pressure overload and represents the substrate for a maladaptive cascade, the so-called AS-related cardiac damage. We hypothesized that in AS patients electrocardiogram (ECG) LVH not only predicts echocardiography LVH but also other noninvasive and invasive markers of cardiac damage and prognosis after aortic valve replacement (AVR). METHODS: In 279 patients with severe AS undergoing ECG, echocardiography, and cardiac catheterization before AVR, the Sokolow-Lyon index, the Cornell product, the Romhilt-Estes score, and the Peguero-Lo Presti score were assessed. RESULTS: The mean left ventricular mass index was 109 ± 34 g/m2 , and 131 (47%) patients had echocardiography LVH. The areas under the receiver operator characteristics curve (AUC) for the Sokolow-Lyon index, the Cornell product, the Romhilt-Estes score, and the Peguero-Lo Presti score for the prediction of echocardiography LVH were 0.59, 0.70, 0.63, and 0.65. The Peguero-Lo Presti score had the numerically greatest AUC for the prediction of left ventricular end-diastolic pressure >15 mmHg, mean pulmonary artery wedge pressure >15 mmHg, pulmonary vascular resistance >3 Wood units, mean right atrial pressure >14 mmHg, and stroke volume index <31 mL/m2 . After a median follow-up of 1365 (interquartile range: 931-1851) days after AVR only the Peguero-Lo Presti score was significantly associated with all-cause mortality [hazard ratio: 1.24 (95% confidence interval: 1.01-1.54); per 1 mV increase; p = .045]. CONCLUSIONS: Among severe AS patients, the Peguero-Lo Presti score is associated with abnormalities in cardiac structure including LVH, invasive measures of cardiac damage, and long-term mortality after AVR.

Impact of Electrocardiographic Parameters on Sudden Death in Patients Receiving Maintenance Hemodialysis: Ten-Year Outcomes of the Q-Cohort Study.

AIM: Sudden death is one of the most common causes of death among hemodialysis patients. Electrocardiography (ECG) is a noninvasive and inexpensive test that is regularly performed in hemodialysis clinics. However, the association between abnormal ECG findings and the risk of sudden death in hemodialysis patients is yet to be fully elucidated. Thus, the aim of this study was to determine the ECG parameters linked to sudden death in patients undergoing hemodialysis. METHODS: The Q-Cohort Study is a multicenter, longitudinal, observational study of hemodialysis patients. In this study, 1,153 Japanese hemodialysis patients aged ≥ 18 years with ECG data recorded within 1 year of study enrollment were followed up for 10 years. Cox proportional hazards models were used to estimate the multivariate-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) for the association between ECG parameters and sudden death. RESULTS: During the median follow-up period of 9.0 years, 517 patients died, 76 of whom exhibited sudden death. After adjusting for confounding factors, higher heart rate, QT prolongation, and left ventricular hypertrophy as per the Sokolow-Lyon voltage criteria were found to be independently associated with an increased risk of sudden death. The adjusted HRs [95% CIs] for each abnormal ECG parameter were 2.02 [1.05-3.89], 2.10 [1.30-1.77], and 1.91 [1.18-3.09], respectively. CONCLUSIONS: Higher heart rate, QT prolongation, and left ventricular hypertrophy on ECG have been determined to be associated with an increased risk of sudden death. Therefore, regular ECG recording could enable medical practitioners to identify hemodialysis patients who require intervention to prevent lethal arrhythmia.

ECG/echo indexes in the diagnostic approach to amyloid cardiomyopathy: A head-to-head comparison from the AC-TIVE study.

BACKGROUND AND AIMS: The discordance between QRS voltages on electrocardiogram (ECG) and left ventricle (LV) wall thickness (LVWT) on echocardiogram (echo) is a recognized red flag (RF) of amyloid cardiomyopathy (AC) and can be measured by specific indexes. No head-to-head comparison of different ECG/echo indexes among subjects with echocardiographic suspicion of AC has yet been undertaken. The study aimed at evaluating the performance and the incremental diagnostic value of different ECG/echo indexes in this subset of patients. METHODS: Electrocardiograms of subjects with LV hypertrophy, preserved ejection fraction and ≥ 1 echocardiographic RF of AC participating in the AC-TIVE study, an Italian prospective multicenter study, were independently analyzed by two cardiologists. Low QRS voltages and 8 different ECG/echo indexes were evaluated. Cohort specific cut-offs were computed. RESULTS: Among 170 patients, 55 (32 %) were diagnosed with AC. Combination of low QRS voltages with interventricular septum ≥ 1,6 cm was the most specific (specificity 100 %, positive predictive value 100 %) ECG/echo index, while the ratio between the sum of all QRS voltages and LVWT <7,8 was the most sensitive and accurate (sensitivity 94 %, negative predictive value 97 %, accuracy 82 %). When the latter index was added to a model using easily-accessible clinical variables, the diagnostic accuracy for AC greatly increased (AUC from 0,84 to 0,95; p = 0,007). CONCLUSIONS: Among patients with non-dilated hypertrophic ventricles with normal ejection fraction and echocardiographic RF of AC, easily-measurable ECG/echo indexes, mainly when added to few clinical variables, can help the physician orient second level investigations. External validation of the results is warranted.

The Neonatal QRS Complex and Its Association with Left Ventricular Mass.

To evaluate QRS complex features during the first month of life and the association with echocardiographic measurements of left ventricular mass in neonates. Prospective cohort study of neonates with electrocardiography (ECG) and echocardiography performed during the first month of life. Left ventricular mass index (LVMI) was determined by echocardiography and the correlation with electrocardiographic markers of LVMI outliers (≥ 98th percentile) were analyzed. We included 17,450 neonates (52% boys; median age at examination 11 days) and found an increase in median QRS duration and LVMI during the first month of life (54 vs. 56 ms and 24.7 vs. 28.6 g/m2 at days 0-4 and 25-30, respectively; both p < 0.001). All investigated ECG features (QRS duration, QRS area in V1/V6, maximum amplitudes of S-V1/R-V6, and the Sokolow-Lyon voltage product) showed no to low correlation with LVMI, resulting in low sensitivities (0-9.0%), but high specificities (97.2-98.1%), and area under the curve values close to the identity line (0.49-0.61) for identifying LVMI outliers. Adjustment of outlier definition for LVMI and threshold for QRS features had no significant effect on sensitivity. We present reference values for QRS complex features and their association with LVMI in neonates from a large, unselected, population-based cohort. The QRS complex gradually evolved during the first month of life but had a low correlation with LVMI. Our results indicate a poor diagnostic value of using ECG features to identify LVMI outliers in neonates.Trial Registry Copenhagen Baby Heart, NCT02753348, https://clinicaltri-als.gov/ct2/show/NCT02753348?cond=Copenhagen+Baby+Heart&draw=2&rank=1 , deidentified individual participant data will not be made available.

Reclassification of Adolescent Ambulatory Prehypertension and Unclassified Blood Pressures by 2022 American Heart Association Pediatric Ambulatory Blood Pressure Monitoring Guidelines.

OBJECTIVE: To describe the epidemiology of reclassification of prehypertensive and unclassified adolescents by 2022 American Heart Association pediatric ambulatory blood pressure monitoring (ABPM) guidelines, and to evaluate the association of the new diagnostic categories with left ventricular hypertrophy (LVH). STUDY DESIGN: A single-center, retrospective review of ABPM reports from adolescents 13-21 years old, from 2015 through 2022, was performed. Adolescents with prehypertension or unclassified by 2014 guidelines were reclassified by 2022 definitions. Logistic regression models evaluated the association of reclassification phenotypes with LVH. RESULTS: A majority of prehypertensive adolescents reclassified to hypertension (70%, n = 49/70). More than one-half (57%, n = 28/49) of the hypertension was isolated nocturnal hypertension, and 80% was systolic hypertension. Reclassification to hypertension was more common in males. The majority (55.6%) of unclassified adolescents were reclassified to normotension. No demographic or clinical variables were associated with reclassification categories. LVH was not associated with hypertension in the reclassified prehypertensive or unclassified groups. CONCLUSIONS: The 2022 ABPM guidelines clearly define blood pressure phenotypes. However, reclassification to hypertension was not associated with an increased odds of LVH. Because most prehypertensive adolescents reclassified as hypertensive by nighttime BPs alone, this study highlights the lowered threshold for nocturnal hypertension. Prospective studies in larger, well-defined cohorts are needed to describe better the predictive value of 2022 BP phenotypes for target organ damage.

Association of lipoprotein(a) with left ventricular hypertrophy assessed by electrocardiogram in adults: a large cross-sectional study.

Background and aims: Increasing evidence supports a causal relationship between lipoprotein(a) [Lp(a)] and atherosclerotic cardiovascular disease, yet its association with left ventricular hypertrophy (LVH) assessed by electrocardiogram (ECG) remains unknown. The aim of this study was to explore the relationship between Lp(a) and LVH assessed by ECG in general population. Methods and results: In this cross-sectional study, we screened 4,052 adults from the participants of the third National Health and Nutrition Examination Survey for analysis. Lp(a) was regarded as an exposure variable. LVH defined by the left ventricular mass index estimated from ECG was considered as an outcome variable. Multivariate logistic regression and restricted cubic spline (RCS) were used to assess the relationship between Lp(a) and LVH. Individuals with LVH had higher Lp(a) compared to individuals without LVH (P< 0.001). In the fully adjusted model, Lp(a) was strongly associated with LVH when as a continuous variable (per 1-unit increment, OR: 1.366, 95% CI: 1.043-1.789, P = 0.024), and higher Lp(a) remained independently associated with a higher risk of LVH when participants were divided into four groups according to quartiles of Lp(a) (Q4 vs Q1, OR: 1.508, 95% CI: 1.185-1.918, P = 0.001). And in subgroup analysis, this association remained significant among participants< 60 years, ≥ 60 years, male, with body mass index< 30 kg/m2, with hypertension and without diabetes (P< 0.05). In addition, we did not observe a nonlinear and threshold effect of Lp(a) with LVH in the RCS analysis (P for nonlinearity = 0.113). Conclusion: Lp(a) was closely associated with LVH assessed by ECG in general population.

Deep Learning Models for Predicting Left Heart Abnormalities From Single-Lead Electrocardiogram for the Development of Wearable Devices.

BACKGROUND: Left heart abnormalities are risk factors for heart failure. However, echocardiography is not always available. Electrocardiograms (ECGs), which are now available from wearable devices, have the potential to detect these abnormalities. Nevertheless, whether a model can detect left heart abnormalities from single Lead I ECG data remains unclear.Methods and Results: We developed Lead I ECG models to detect low ejection fraction (EF), wall motion abnormality, left ventricular hypertrophy (LVH), left ventricular dilatation, and left atrial dilatation. We used a dataset comprising 229,439 paired sets of ECG and echocardiography data from 8 facilities, and validated the model using external verification with data from 2 facilities. The area under the receiver operating characteristic curves of our model was 0.913 for low EF, 0.832 for wall motion abnormality, 0.797 for LVH, 0.838 for left ventricular dilatation, and 0.802 for left atrial dilatation. In interpretation tests with 12 cardiologists, the accuracy of the model was 78.3% for low EF and 68.3% for LVH. Compared with cardiologists who read the 12-lead ECGs, the model's performance was superior for LVH and similar for low EF. CONCLUSIONS: From a multicenter study dataset, we developed models to predict left heart abnormalities using Lead I on the ECG. The Lead I ECG models show superior or equivalent performance to cardiologists using 12-lead ECGs.

[New guidelines on the diagnostic and therapeutic management of hypertrophic cardiomyopathy]. / Nouvelles recommandations pour le diagnostic et la prise en charge thérapeutique de la cardiomyopathie hypertrophique.

Hypertrophic cardiomyopathy is a disease characterized by left ventricular hypertrophy (with or without right ventricular hypertrophy) not explained by loading conditions, the origin of which may be genetic and whose phenotypic expression is highly variable. The novelties in terms of diagnosis, clinical development, and management have been the subject of an update of the recommendations of the European Society of Cardiology (ESC).

La cardiomyopathie hypertrophique est une maladie caractérisée par une hypertrophie ventriculaire gauche (avec ou sans hypertrophie ventriculaire droite) non expliquée par les conditions de charge, dont l'origine peut être génétique et dont l'expression phénotypique est très variable. Les nouveautés en termes diagnostique, de mise au point, et de prise en charge ont fait l'objet d'une mise à jour des recommandations de la Société Européenne de Cardiologie (ESC).